Interneuron Diversity in Layers 2–3 of Monkey Prefrontal Cortex
Bibliographic record
Abstract
The heterogeneity of gamma-aminobutyric acid interneurons in the rodent neocortex is well-established, but their classification into distinct subtypes remains a matter of debate. The classification of interneurons in the primate neocortex is further complicated by a less extensive database of the features of these neurons and by reported interspecies differences. Consequently, in this study we characterized 8 different morphological types of interneurons from monkey prefrontal cortex, 4 of which have not been previously classified. These interneuron types differed in their expression of molecular markers and clustered into 3 different electrophysiological classes. The first class consisted of fast-spiking parvalbumin-positive chandelier and linear arbor cells. The second class comprised 5 different morphological types of continuous-adapting calretinin- or calbindin-positive interneurons that had the lowest level of firing threshold. However, 2 of these morphological types had short spike duration, which is not typical for rodent adapting cells. Neurogliaform cells (NGFCs), which coexpressed calbindin and neuropeptide Y, formed the third class, characterized by strong initial adaptation. They did not exhibit the delayed spikes seen in rodent NGFCs. These results indicate that primate interneurons have some specific properties; consequently, direct translation of classification schemes developed from studies in rodents to primates might be inappropriate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".